Title :
Voice pathology detection with MDVP parameters using Arabic voice pathology database
Author :
Al-nasheri, Ahmed ; Ali, Zulfiqar ; Muhammad, Ghulam ; Alsulaiman, Mansour ; Almalki, Khalid H. ; Mesallam, Tamer A. ; Farahat, Mohamed
Author_Institution :
Dept. of Comput. Eng., King Saud Univ., Riyadh, Saudi Arabia
Abstract :
This paper investigates the use of Multi-Dimensional Voice Program (MDVP) parameters to automatically detect voice pathology in Arabic voice pathology database (AVPD). MDVP parameters are very popular among the physician / clinician to detect voice pathology; however, MDVP is a commercial software. AVPD is a newly developed speech database designed to suit a wide range of experiments in the field of automatic voice pathology detection, classification, and automatic speech recognition. This paper is the first step to evaluate MDVP parameters in AVPD using sustained vowel /a/. The experimental results demonstrate that some of the acoustic features show an excellent ability to discriminate between normal and pathological voices. The overall best accuracy is 81.33% by using SVM classifier.
Keywords :
medical signal detection; signal classification; speech recognition; support vector machines; AVPD; Arabic voice pathology database; MDVP parameters; SVM classifier; acoustic features; automatic speech recognition; commercial software; multidimensional voice program; speech database; support vector machine; voice pathology detection; Accuracy; Acoustics; Databases; Pathology; Speech; Speech recognition; Support vector machines; AVPD; MDVP; MEEI; SVM; voice pathology detection;
Conference_Titel :
Information Technology: Towards New Smart World (NSITNSW), 2015 5th National Symposium on
Conference_Location :
Riyadh
Print_ISBN :
978-1-4799-7625-6
DOI :
10.1109/NSITNSW.2015.7176431